Brandon Beattie, PA-C and Physician Associate educator at The George Washington University School of Medicine and Health Sciences, piloted ibl.ai with his graduate medical students this semester, and the results speak for themselves.
Developed in collaboration with ibl.ai, the ibl.ai is reshaping how future clinicians review complex material, practice board questions, and, crucially, how faculty monitor learning in real time.
"As a physician associate educator, I teach graduate medical students, and I was really pleased with ibl.ai. I like that I was able to upload my own materials. A secondary gain from this is that I could see in real time the questions that the students were posing. I could check in and police the responses if they went too far into the weeds. But as an educator, I also used it as a tool to be able to see and analyze these ideas that were being put into the agent, touching on some topics that maybe remained a little murky.
Additionally, what I think worked really well is that it encouraged the students to do self-assessments and create practice questions. There's an art to that, and I was really impressed with how well ibl.ai was able to use my materials and internet resources to create great board questions for the students."
- Brandon Beattie, PA-C
Key Achievements and Success Stories
High-Quality Board Practice Questions
ibl.ai autogenerates USMLE-style items from instructor resources and trusted medical references.
Students build self-assessment banks aligned to exam blueprints.
Real-Time Visibility into Student Thinking
Live question feed & analytics reveal where concepts remain murky.
Faculty can “police” answers or refine prompts on the fly.
Instructor Control & Medical-Grade Alignment
Upload lecture slides, guidelines, and journal PDFs—responses stay grounded in faculty-approved sources.
Adjustable system prompts ensure an evidence-based, clinically appropriate tone.
Enhanced Student Engagement & Self-Assessment
24/7 tutoring means learners can quiz themselves whenever motivation strikes.
Encourages metacognition by having students write their own practice questions before comparing with the AI’s version.
How It Works
GWU’s implementation partner, ibl.ai provides an application-layer, language-model-agnostic solution that:
Works with OpenAI, Gemini, Llama, Anthropic, or any LLM your institution prefers.
Embeds in Canvas, Blackboard, or any LTI-compatible LMS in minutes.
Gives institutions full code & data ownership plus deep analytics dashboards.
Delivers personalized, 24/7 support on web, iOS, and Android.
For more information about ibl.ai AI Agents and to start for free on web, iOS and Android, please visit ibl.ai for Higher Education or message our team.